Fuzzy XML Data Management, Li Yan; Zongmin Ma; Fu Zhang

Автор: Carlsson, Christer Fedrizzi, Mario Fuller, Robert
Название: Fuzzy logic in management
ISBN: 1461347440 ISBN-13(EAN): 9781461347446
Издательство: Springer
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Описание: This book shows how the application of fuzzy logic can benefit management, group decision making, strategic planning, supply chain management and other business imperatives.

Автор: Olga Pons; Maria A. Vila
Название: Knowledge Management in Fuzzy Databases
ISBN: 3790824674 ISBN-13(EAN): 9783790824674
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Описание: reflections which have been suggested to me by some words in the following articles such as: graded notions, fuzzy objects, uncertainty, fuzzy implications, fuzzy inference, empty intersection, etc.

Автор: Nikos Pelekis; Yannis Theodoridis
Название: Mobility Data Management and Exploration
ISBN: 1493903918 ISBN-13(EAN): 9781493903917
Издательство: Springer
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Описание: This text integrates different mobility data handling processes, from database management to multi-dimensional analysis and mining, into a unified presentation driven by the spectrum of requirements raised by real-world applications.

Автор: Markus Helfert; Andreas Holzinger; Orlando Belo; C
Название: Data Management Technologies and Applications
ISBN: 3319259350 ISBN-13(EAN): 9783319259352
Издательство: Springer
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Описание: This book constitutes the thoroughly refereed proceedings of the Third International Conference on Data Technologies and Applications, DATA 2014, held in Vienna, Austria, in August 2014. The 12 revised full papers were carefully reviewed and selected from 87 submissions.

Автор: Zongmin Ma; Li Yan
Название: Soft Computing in XML Data Management
ISBN: 3642264018 ISBN-13(EAN): 9783642264016
Издательство: Springer
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Описание: This book covers in a great depth the fast growing topic of techniques, tools and applications of soft computing in XML data management. It shows how XML data management (like model, query, integration) can be covered with a soft computing focus.

Автор: Carlo Bertoluzza; Maria A. Gil; Dan A. Ralescu
Название: Statistical Modeling, Analysis and Management of Fuzzy Data
ISBN: 3790825018 ISBN-13(EAN): 9783790825015
Издательство: Springer
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Описание: The contributions in this book state the complementary rather than competitive relationship between Probability and Fuzzy Set Theory and allow solutions to real life problems with suitable combinations of both theories.

Автор: Alexander Gegov
Название: Complexity Management in Fuzzy Systems
ISBN: 3642072518 ISBN-13(EAN): 9783642072512
Издательство: Springer
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Описание: Doing research is a great adventure As any adventure sometimes it is hard You may feel alone and with no idea where to go But if you have courage and press onwards You will eventually stand where no one has stood And see the world as no one has seen it There can be no better feeling than this Adaptation from 'Introduction to Research', Tom Addis (2004) The idea about this book has been on the author's mind for almost a decade but it was only about a couple of years ago when the underlying research process was actually started. The reason for this delay has been the insufficient spare time for research being a lecturer in a 'new' UK university where the emphasis is mainly on teaching. And maybe this book would have never been written if the author had not been presented with the chance of developing new teaching modules in fuzzy logic that have given him food for thought in a research related context and have helped him combine efficiently his teaching and research activities. The title of this book may sound too specialised but it has a much wider meaning. Fuzzy systems are any systems for modelling, simulation, control, prediction, diagnosis, decision making, pattern recognition, image processing, etc. which use fuzzy logic. Although fuzzy logic is an advanced extension of binary logic, the latter is still used predominantly today.

Автор: Athena Vakali; Lakhmi C Jain
Название: New Directions in Web Data Management 1
ISBN: 3642266908 ISBN-13(EAN): 9783642266904
Издательство: Springer
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Описание: This volume addresses the major issues in Web data management related to technologies and infrastructures, methodologies and techniques as well as applications and implementations. Emphasis is placed on Web engineering and technologies, Web graph managing, searching and querying.

Автор: Niu
Название: Data-Driven Technology for Engineering Systems Health Management
ISBN: 9811020310 ISBN-13(EAN): 9789811020315
Издательство: Springer
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Описание: This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.

Автор: Li Yan; Zongmin Ma; Fu Zhang
Название: Fuzzy XML Data Management
ISBN: 3642448984 ISBN-13(EAN): 9783642448980
Издательство: Springer
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Описание: This book details recent advances in fuzzy XML data management. Coverage includes: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models and reasoning of fuzzy XML.

Автор: Bing-Yuan Cao; Sheng-Quan Ma; Hu-hua Cao
Название: Ecosystem Assessment and Fuzzy Systems Management
ISBN: 3319034480 ISBN-13(EAN): 9783319034485
Издательство: Springer
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Описание: "Ecosystem Assessment and Fuzzy Systems Management" is the edited outcome of the 3rd International Conference on Ecosystem Assessment Management (ICEAM) and the Workshop on the Construction of an Early Warning Platform for Eco-tourism (WCEWPE) in Hainan on May 5-12, 2013, Haikou, China.

Автор: Deng-Feng Li
Название: Decision and Game Theory in Management With Intuitionistic Fuzzy Sets
ISBN: 3662514265 ISBN-13(EAN): 9783662514269
Издательство: Springer
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Описание:

Chapter 1 Intuitionistic Fuzzy Set Theories

1.1 Introduction

1.2 Intuitionistic Fuzzy Sets and Operations

1.3 Intuitionistic Fuzzy Set Distances and Similarity Degrees

1.3.1 Definition of Similarity Degrees between Intuitionistic Fuzzy Sets

1.3.2 Definition of Distances between Intuitionistic Fuzzy Sets

1.4 Representation Theorem of Intuitionistic Fuzzy Sets

1.5 Extension Principle of Intuitionistic Fuzzy Sets and Operations

1.5.1 Extension Principle of Intuitionistic Fuzzy Sets

1.5.2 Operations over Intuitionistic Fuzzy Sets

1.6 Definitions of Intuitionistic Fuzzy Numbers and Algebraic Operations

1.6.1 Trapezoidal Intuitionistic Fuzzy Numbers and Algebraic Operations

1.6.2 Triangular Intuitionistic Fuzzy Numbers and Algebraic Operations

Chapter 2 Intuitionistic Fuzzy Set Aggregation Operators and Multiattribute Decision Making Methods

2.1 Introduction

2.2 Intuitionistic Fuzzy Set Aggregation Operators and Properties

2.2.1 Intuitionistic Fuzzy Set Weighted Aggregation Operators

2.2.2 Intuitionistic Fuzzy Set Hybrid Weighted Aggregation Operators

2.2.3 Intuitionistic Fuzzy Set Generalized Hybrid Weighted Aggregation Operators

2.3 Intuitionistic Fuzzy Set Generalized Hybrid Weighted Aggregation Method for Intuitionistic Fuzzy Set Multiattribute Decision Making

2.3.1 Formal Representation of Intuitionistic Fuzzy Set Multiattribute Decision Making Problems

2.3.2 Intuitionistic Fuzzy Set Multiattribute Decision Making Process Based on Intuitionistic Fuzzy Set Generalized Hybrid Weighted Aggregation Operators and Real Example Analysis

Chapter 3 Intuitionistic Fuzzy Set Multiattribute Decision Making Methods

3.1 Introduction

3.2 Linear Weighted Average Method for Multiattribute Decision Making with Both Weights and Attribute Ratings Expressed by Intuitionistic Fuzzy Sets

3.2.1 Linear Weighted Average Model of Intuitionistic Fuzzy Set Multiattribute Decision Making

3.2.2 Sensitivity Analysis of Linear Weighted Average Method for Intuitionistic Fuzzy Set Multiattribute Decision Making

3.2.3 Process of Linear Weighted Average Method for Intuitionistic Fuzzy Set Multiattribute Decision Making and Real Example Analysis

3.3 TOPSIS for Intuitionistic Fuzzy Set Multiattribute Decision Making with Both Ideal Solutions and Weights Known

3.3.1 Basic Principle of TOPSIS

3.3.2 Intuitionistic Fuzzy Set TOPSIS Principle and Real Example Analysis

3.4 Optimum Seeking Method for Intuitionistic Fuzzy Set Multiattribute Decision Making with Both Ideal Solutions and Weights Known

3.4.1 Optimum Seeking Principle for Intuitionistic Fuzzy Set Multiattribute Decision Making

3.4.2 Process of Optimum Seeking Method for Intuitionistic Fuzzy Set Multiattribute Decision Making and Real Example Analysis

3.5 Linear Programming Method for Multiattribute Decision Making with Both Weights and Attribute Ratings Expressed by Intuitionistic Fuzzy Sets

3.5.1 Allocation Method of Hesitancy Degrees

3.5.2 Linear Programming Models and Method for Computing Intuitionistic Fuzzy Set Comprehensive Evaluations

3.5.3 Relative Closeness Degree Method of Intuitionistic Fuzzy Set Comprehensive Evaluations and Real Example Analysis

3.6 LINMAP for Intuitionistic Fuzzy Set Multiattribute Decision Making with Both Ideal Solutions and Weights Unknown

3.6.1 Determination Methods of Membership and Nonmembership Degrees of Intuitionistic Fuzzy Sets

3.6.2 Consistency and Inconsistency Measure Methods

3.6.3 LINMAP Models for Intuitionistic Fuzzy Set Multiattribute Decision Making

3.6.4 LINMAP Process for Intuitionistic Fuzzy Set Multiattribute Decision Making and Real Example Analysis

3.7 Fraction Mathematical Programming Method for Intuitionistic Fuzzy Set Multiattribute Decision Making with Unknow